Journal of Urban Planning and Development

Mobility inequality is prevalent in different levels of severity in most of the development occurring worldwide. The rapid expansion of research on this topic in the last few decades has compelled scholars to comprehensively review the relevant literature. However, a bibliometric understanding of this field has not yet been conducted. We performed a bibliometric analysis of 578 articles on the subject published between 2002 and 2023, retrieved from the Web of Science, to identify and review the most influential literature. Descriptive and network analysis was carried out using Bibliometrix and VOSviewer software. Insights were derived regarding the most prominent authors, sources, countries, and keywords. Future research directions on mobility inequality are also proposed. We found that accessibility is a significant research cluster in mobility inequality research and has enough potential for further development. Further, a content analysis of 48 relevant articles under the accessibility cluster was conducted. Our study is limited to a bibliometric overview and a review of key literature and does not provide an in-depth review of the whole literature. However, it can aid scholars in understanding the trends and patterns of research development on mobility inequality and in identifying research gaps and future research themes.

The development of urban rail transit systems is progressing rapidly, and an increasing number of cities worldwide are either in the process or planning to construct urban rail transit systems. However, questions arise as to whether all cities truly require such systems and how to prevent these transit systems from becoming decorative rather than essential to urban development. This paper collates various antecedent conditions that may influence ridership in rail transit across 31 cities in China with operating rail transit. To this end, it uses two main methods, including necessary condition analysis and fuzzy-set qualitative comparative analysis methodologies. In this way, it explores the interactive effects of multiple factors such as the level of urban development, trends in urban development, ground-level road network congestion, urban spatial patterns (centrality), coverage of rail transit, and government focus on rail transit. The results show that no single antecedent condition can be a necessary condition for high ridership in rail transit. Rather, the effective combination of various antecedent conditions has elevated postimplementation ridership in a different means, same end manner. Moreover, the government's focus on rail transit development or its effective planning can increase postimplementation ridership in cities lacking some objective resource conditions. Furthermore, ridership in most cities remains stable after the initiation of rail transit. The findings imply that the development of urban rail transit systems requires a comprehensive urban development plan, which covers urban growth trends, congestion levels, and spatial patterns.

This study examined the impact of land use–land cover (LULC) on land surface temperature (LST) and the urban heat island effect in Nowshera District, Pakistan, from 2008 to 2018. The study utilized remotely sensed data for computing various LULC types and land surface temperatures. The supervised classification suggests a significant shift in LULC of the study area, i.e., built-up areas expanded from 14.8% to 22.8%, while vegetation decreased from 60.08% to 56.08%. The same was observed for LST, which rose from 35.39°C to 39.96°C from 2008 to 2018. The mean LST in Nowshera increased by a substantial 5.4°C during the study period. The results revealed that LST has been rising steadily since 2008 and that built-up and vacant land consistently experiences the highest LST. Additionally, the study showed that the built environment had a significant effect on LST. The findings underscore a direct link between LULC changes and LST variations. The study highlights the urgency of regulating land-use–land cover changes through constant monitoring and planning to mitigate detrimental consequences. This can improve Nowshera District's resilience and livability, providing a sustainable urban environment for its residents.

Urban green spaces (UGSs) have potential significance for urban ecosystems, as they provide environmental benefits and benefits for residents' physical activity and mental health. Objective assessments of UGSs are necessary for optimizing the allocation of green space public resources and providing a basis for social equality. Previous studies have adopted a few indicators to evaluate UGS provision but have neglected multidimensional interaction characteristics. This study proposes a framework that integrates principal component analysis and the spatial clustering method to identify geographically homogeneous subregions with similar characteristics, including dimensions of accessibility, ecological function, quality, and quantity. Shenzhen, China, was selected as a case study, and the results indicate the following: (1) the multiple dimensions of UGSs are unevenly distributed, and it is necessary to evaluate UGSs from multiple dimensions; and (2) there are significant disparities in UGSs among different clusters that can be summarized to guide the improvement of green space equity. It is necessary to increase the number of community parks and optimize the green view index in more densely populated areas and the outskirts. Our study provides an intuitive and comprehensive evaluation framework for the distribution of UGSs and identifies their characteristics in different subregions, which is valuable for space quality improvement and reasonable zoning planning.

Urban renewal is the result of collaborative governance among multiple stakeholders, and identifying the matching relationship between different urban renewal models and their performance is conducive to a more precise allocation of resources for urban renewal in various cities. In this study, we constructed a six-dimensional framework of benefits, covering local government, the regional economy, cultural preservation, social governance, ecological protection, and the role of cities. The work encompassed 18 evaluation indicators driving urban renewal based on urban renewal data from 20 cities in China. We employed the entropy weight and fuzzy set qualitative comparative analysis (fsQCA) methods to develop three urban renewal performance driving models—the comprehensive development model, political–ecological synergistic driving model, and economic–cultural weakness model. Furthermore, we categorized the characteristics of urban renewal in the 20 cities, providing theoretical support for the tailored formulation of differentiated urban renewal strategies based on each city’s development status.

The level of preparedness of communities to heat-related consequences varies. While several studies have developed heat vulnerability indices, little-to-no research efforts were directed to assess the heat resilience of communities. To that extent, this paper develops and validates a heat resilience index (HRI). First, a dataset of 44 indicators affecting heat resilience was collected and grouped into five categories: sociodemographic, land use/land cover (LULC), health facilities, meteorological, and geographic factors. Second, principal component analysis (PCA) was used to calculate the weights or importance of each indicator. Based on the calculated weights, five heat resilience subindices were developed for the five categories. Third, the overall HRI was developed as a weighted average of the five calculated subindices. Fourth, the developed HRI was scientifically validated based on real-world heat-related illnesses data. The HRI was demonstrated for the State of New Jersey, where the results showed that more than 71% of the studied census tracts have a poor resilience toward heat waves. Furthermore, the results highlighted that the following indicators affect heat resilience the most: median income, poverty, percentage of people younger than 5 years old, land area, building area, annual Normalized Difference Vegetation Index (NDVI), summer NDVI, number of hospitals, mean annual temperature, minimum temperature, maximum temperature, and urban elevation. Also, the results identified the LULC category as the most influential category on the overall heat resilience. The findings could assist in developing appropriate heat management and mitigation plans to enhance communities' ability to resist future heat waves, where the same method could be used to assess heat resilience for other states and countries worldwide through developing the associated dataset. Ultimately, this research adds to the body of knowledge by proposing a structured framework for developing a novel heat resilience index based on a comprehensive list of 44 indicators.

The rapid urbanization and subsequent motorization experienced in India have profound negative implications on the environment due to increased exhaust emission levels. India is one of the biggest global markets for the motorized two-wheeler (M2W) segment. Therefore, replacing M2Ws with electric two-wheelers (E2Ws) is considered essential to mitigate the adverse effects on the environment. However, developing the required infrastructure to support the operation, especially as desired by the prospective users, is essential to accelerate the acceptance of E2Ws by Indian commuters. Therefore, a travel behavior–based investigation was carried out in this study to evaluate the prospective users’ preferences for the E2W infrastructure-specific attributes. The preferences were investigated in terms of willingness to pay (WTP) for the improvement of infrastructure attributes. The WTP is generally considered a measure of user benefit associated with a specific attribute. For the stated purpose, a stated preference experiment was designed, and preferences of the prospective users for different infrastructure settings were collected from E2W prospective users in Hyderabad. The preference data were analyzed by developing appropriate discrete choice models, namely, multinomial logit and random parameter logit (RPL) models. Further, the influence of socioeconomic and trip characteristics of the prospective E2W users on the infrastructure attributes was also evaluated by examining the heterogeneity around the means of random parameters in the RPL model. The results reveal that prospective users have a higher WTP for improving the public charging infrastructure and parking infrastructure availability. Characteristics such as gender, age, and journey time significantly influence the prospective E2W users’ WTP associated with infrastructure attributes. Based on the results and inferences, the necessary policy measures for developing adequate infrastructure for E2Ws are also presented in this study.

Stress is considered one of the foremost essential components in expanding city mental disarranges. In comparison, creating cities that are more compatible with stress has been the focus of many governments, organizations, and researchers. Nevertheless, there are fewer empirical studies in this field. Hence, the present study aims to identify stressors in Zone 8, Municipal District 1 of Tehran, Iran. This study is focused on the descriptive-explanatory research. The data are collected using quantitative–qualitative methods and analyzed by factor analysis and multivariate regression. The findings indicate that the factors identified by factor analysis explain 66.8% of the changes in urban stress reported by citizens. Moreover, in the studied area, 19 factors are identified as the causes of urban stress, as follows (in order of importance): social differentiation and social isolation, lack of security, neighborhood quality, access to mental health-improving places, being able to satisfy and deal with emotions, control and prediction of the environment, the presence of open and green spaces, high-rise construction, social deprivation, stressful urban design, residents’ social status, resilience, access to centers and services, substance exposure and abuse, spatial diversity, deprivation, socioeconomic station, urban health, and being an ethnic minority. As a result, trying to control them makes it possible to reduce urban stress significantly.

Abstract

Recreational open spaces (ROS), as essential public amenities, provide a multitude of benefits for city residents. The rapid growth of urban population is raising significant concerns about diminishing green infrastructure, shifts in land use, and erosion of valuable ecosystem services. This necessitates the equitable allocation of green infrastructure in appropriate proximity to the city residents. This study assessed disparity in ROS distribution, considering both availability and accessibility at varying administrative levels. The distribution is assessed with respect to resident population, providing special regard to the adolescent age group. Study is conducted taking Bhopal, India as the case. The Green Space Index and the Lorenz curve are utilized to assess social equity of ROS distribution. In addition, location quotient is employed to assess spatial equity concerning ROS distribution with respect to distribution of resident population. The study outcome illustrates that urban park accessibility varies at different administrative levels. Analysis reveals that higher number of ROS do not necessarily translate to higher ROS accessibility, especially for the adolescent age group. This is due to the inadequate size and proximity of ROS to residents, particularly in recent developments. A participatory GIS survey of 651 adolescents is conducted to further confirm the preceding spatial analyses by exploring associations between ROS accessibility and adolescents ROS visits. The prevailing urban ROS planning in India and several developing nations primarily relies on per capita availability and ratios of ROS to developed land. This approach alone is insufficient. The study results hold vital implications and can be incorporated in the existing urban ROS guidelines. This analysis is pivotal for sustainable ROS planning and policy-making, aiming to achieve environmental and social sustainability, centered on population, especially adolescents.

Practical Applications

This study centers on assessing the spatial allocation of ROS with a focus on equity considerations. The particular emphasis lies in examining how well the spatial distribution of ROS aligns with the requirements of its population in the same planning region. The outcomes of this investigation reveal that the conventional metrics used in ROS planning, namely the per capita ROS area and ratio of ROS to urban land, do not adequately capture the equity dimensions of ROS provision. The results reveal that spatial misalignment exists in the allocation of ROS and its distribution among the population, especially among adolescents. Furthermore, the results highlight that urban growth and densification can result in a general decline in urban green infrastructure. Such results will help to implement green initiatives across identified administrative levels to enhance the wellbeing of residents with an understanding of the population distribution within a region.

This study investigates the impact of urban greenspace on the settlement intention of domestic migrants in China. We find that urban greenspace increases migrants’ intention to stay long term in the area where they currently live. This positive impact is greater for migrants aged 45–60, with nonagricultural household registration, interprovincial migration, and more educated and higher income. We also empirically test two mechanisms through which urban greenspace affects migrants’ settlement intention–health effect and emotional effect. Moreover, we demonstrate that the positive impact of greenspace on settlement intention can be offset by crowded areas. This study expands the research field of environment and migration, providing valuable practical significance for urban ecological environment construction and the improvement of domestic migrants’ management in China.

Numerous shrinking cities have emerged in the new development stage of China, and the authorities have tried to adopt the policy pool of abolishing counties and establishing districts to alleviate urban shrinkage. This study uses urban nighttime light data from 2010 to 2017 to determine whether the policy is effective in a Difference-in-Difference model framework. We find that China's urban shrinkage shows a shrinkage–expansion cycle, and the policy of removing counties and establishing districts has a significant effect on the population of the counties, which indicates that the policy can ease urban shrinkage. Specifically, the positive effect is stronger for counties belonging to cities with higher administrative rank, and for cities located in the East region and Southwest region. Our study has great practical implications for the governance of shrinking cities and promoting sustainable urban development.

In the past, for urban governance issues, local governments tended to only focus on the economic development of cities, but in recent years, in the context of the global pursuit of sustainable goals, how to propose public investment policies that can attract more people willing to relocate to cities has become more important. This paper explores the impact of public investment with different goals (types) on urban development to illustrate that public investment only in pursuit of economic development (income growth) may result in cities deviating from achieving their sustainable goals. Excessive housing prices and pollution may reduce people’s willingness to move there. Only investing in both economic development and infrastructure that can improve the living environment may enable cities’ housing prices and populations to grow moderately. By constructing a theoretical model and numerical simulation analysis, this paper not only explains the positive and negative externalities of public investment but also proposes what factors affect cities’ housing prices, population, and the benefits of public investment. The results of this paper can help local governments formulate urban governance policies and supplement the literature on sustainable cities.

The development of smart cities plays a crucial role in facilitating the integration of economic and ecological benefits within urban contexts. However, whether this could benefit firms has received limited attention in existing studies. This study aims to investigate the relationship between smart city pilots (SCPs) and corporate total factor productivity (TFP), examining the potential mechanisms and different heterogeneities. Utilizing a difference-in-difference strategy with Chinese listed firms’ data from 2005 to 2020, a quasi-natural experiment was conducted to test the proposed hypotheses based on the three batches of SCPs in China from 2012 to 2014. The empirical analyses showed that SCPs can significantly decrease corporate TFP (β = −0.075, p < 0.01). It was further revealed that this association is mediated by corporate governance practices (z = −2.4, p < 0.05). Moreover, the results uncovered the presence of heterogeneities, particularly concerning geographical location and urban scale, with a stronger inhibitory impact on TFP in the eastern region and supercities. These findings provide empirical evidence supporting the Solow paradox theory and furnish insightful references for other similar developing countries to refine the strategies in smart city development, thereby achieving more favorable outcomes.

Urban agglomeration development planning policy (referred to as planning policy in this paper) played a significant role in promoting regional economic development. However, an important issue is whether this planning policy promotes the efficiency of urban economic development. Therefore, based on panel data sets that cover 283 cities from 2007 to 2019, this paper used the planning policy that was approved by the China State Council as a quasi-natural experiment to investigate the effect of this planning policy on the efficiency of urban economic development. The results primarily found that the effect mechanisms of this planning policy on the efficiency of urban economic development contained two paths, which included the intermediary effects of industrial agglomeration and government action. In addition, the results showed that this planning policy played a leading role in influencing the efficiency of urban economic development with the concentration of secondary industries; however, implementing this planning policy did not improve the efficiency of urban economic development. In addition, the results show that the gap in economic development efficiency between cities was narrowing, and implementing this planning policy would facilitate the narrowing trend. Finally, to promote the high-quality development of the urban economy, this paper provides the targeted policy implications.

Given China's new-type urbanization and green transformation, effective control of haze pollution has assumed paramount importance. However, the two-way effects of new-type urbanization, economic development, and haze pollution from a spatial and temporal perspective have not been well explored. Using panel data from 2009 to 2020 for 278 Chinese cities, we applied spatial simultaneous equation models and the generalized spatial three-stage least squares approach to investigate the interactions among new-type urbanization, economic development, and haze pollution. Then, temporal heterogeneity analysis was conducted to discuss changes in the interactions. The findings revealed the following: (1) There was a bidirectional connection between new-type urbanization and economic development. Moreover, the favorable influence of new-type urbanization on economic development enhanced from 2009 to 2020, with the coefficient rising from 0.95 to 1.38. Interestingly, it was only during the Period 2015–2020 that new-type urbanization had a radiative impact on economic growth in the surrounding areas. (2) A 1% increase in new-type urbanization and economic development resulted in 0.71% and 0.91% increase in haze pollution, respectively. Nonetheless, with the new-type urbanization construction, the haze-reducing effects gradually appeared. (3) Considering the reverse effects, severe haze pollution was detrimental to new-type urbanization and economic development. Notably, this inhibitory effect was underestimated when neglecting spatial effects. This study's findings could provide empirical evidence for promoting sustainable urban development and haze pollution reduction in China.

The study of the spatiotemporal evolution of regional development plays a vital role in regional coordination and sustainable development, and analyzing the characteristics of the spatiotemporal evolution of regional development in Jiangxi Province is of great significance for its deep integration into the Yangtze River Delta, the Pearl River Delta, and Fujian, and its active undertaking of industries in developed regions. Based on the National Polar-orbiting Partnership–Visible Infrared Imaging Radiometer Suite (NPP-VIIRS)-like nighttime lighting data from 2003 to 2022, this paper explores and discusses the nighttime lighting data as an effective indicator of regional development from the perspective of Jiangxi Province as a whole, using correlation analysis and multiple linear regression. Meanwhile, the spatial and temporal evolution characteristics of regional development in Jiangxi Province are explored by using spatial autocorrelation, hotspot analysis, standard deviation ellipse, and other research methods in 100 counties in Jiangxi Province. The results show the following: (1) The nighttime lighting data in Jiangxi Province shows a strong positive correlation with gross domestic product (GDP) and total population data, with correlation coefficients R² of 0.957 and 0.896, respectively. (2) The GDP and total population of Jiangxi Province significantly impact nighttime lighting, and the regression model R² reaches 0.983, indicating that the class NPP-VIIRS nighttime lighting data has an excellent explanatory ability for the regional development of Jiangxi Province. (3) The global autocorrelation index of nighttime lighting in each county in Jiangxi Province shows a significant positive correlation level. However, the value of this index still shows a gradually decreasing trend, indicating that the spatial heterogeneity is gradually increasing. As a whole, the hotspots in Jiangxi Province are mainly dominated by the city of Nanchang and supplemented by Ganzhou city, showing the development of two centers in the north and south. (4) The change in the trajectory of the center of gravity migration from 2003 to 2011 is also more apparent, with greater changes in the direction of regional development in Jiangxi Province. In the period 2012–2022, the direction of regional development is more stable, and the change in the migration of the center of gravity tends to be stable, indicating that the direction of regional development is clear at this stage, and there is little change in the overall direction of the economy and centripetal force. The study results provide important clues for an in-depth understanding of the regional development law in Jiangxi Province and are of some reference significance for relevant decision-making and planning.

Urban agglomerations, emerging as pivotal spatial units, increasingly attract essential production factors—talent, technology, and capital—thereby transforming cities into innovation hubs. This study critically examined how productive service agglomeration, through the lens of agglomeration economies and externalities, acts as a catalyst for urban technological advancement. It investigated the spatial effects and underlying mechanisms by which productive service industry agglomerations impact urban technological innovation. Our findings reveal that both specialized and diversified agglomerations significantly enhance urban technological capabilities. However, diversified agglomerations might also negatively impact surrounding areas, revealing a complex spatial interplay. Importantly, while the aggregation of productive services boosts innovation by attracting R&D talent, it does not similarly influence the movement of R&D capital, thereby limiting further technological advancements. The effects of specialized and diversified agglomerations vary across different urban scales and regions. In China, although the productive service industry largely comprises lower-end sectors like finance, leasing, and business services, high-end tech industries remain underdeveloped, lacking robust growth momentum. This study underscores a critical gap in understanding the differential impacts of service industry agglomerations on urban innovation ecosystems and emphasizes the need for nuanced policy interventions to optimize these dynamics for sustainable urban and technological development.

In urban signalized intersections, because of the mixing of straight-going and right-turn vehicles in the straight-right shared lane, the straight traffic may block the rear right-turn vehicles from crossing the intersection during the red light, resulting in additional waiting time for right-turn vehicles. To address this problem, this study proposed the dynamic straight-right lane (DSRL) design and corresponding signal control schedule, which separates the straight-going and right-turn vehicles in space–time, making vehicles enter the intersection in an orderly manner. Then, the key parameters of the signal timing scheme were identified, and the physical significance of the key parameters of the optimal signal timing and the calculation models were given by discussing the optimal process of traffic flow operation at the signalized intersection. Finally, taking a realistic T-shaped signal intersection inlet lane as an example, the simulation verification platform was built by VISSIM to analyze the effects of variables on the performance of the DSRL proposed in this study. The results showed that the design proposed in this study can significantly reduce the right-turn vehicle delay without changing the overall layout of the signal intersection, and the total delay optimization rate at the intersection can always reach 10%–30%.

The urban space community is the basic unit used to demonstrate the urban spatial structure, and the space community structure of island-oriented cities is different from that of general inland cities because they are formed based on the island and the inland, respectively. Through the case study of Xiamen, based on smart card data, this paper divides the obtained origin–destination data into local and global levels with trip cutoff thresholds. The distribution of city centers is analyzed by detecting the overall urban space community structure and the two-level intraisland and cross-island urban space community structure with the PageRank and community detection algorithms. The results revealed that: (1) in the spatial structure of the island-oriented city, the cores are clustered on the island, while the centers are distributed in bands and dots outside the island; (2) the community units are distributed across the island; and (3) the space community boundary of the island-oriented city is quite different from the artificially defined administrative unit boundary. To summarize, by enhancing the delineation of urban spatial communities using the Gaussian kernel function and least-squares cross-validation, improving the model granularity, and integrating data from multiple public transport modes, this paper achieved a more precise division of urban spatial community structures. Consequently, it revealed the distinctive urban form and developmental pattern of the island-oriented city, holding significant implications for investigating urban spatial layout studies.

Urban sprawl has a significant impact on the air environment. In this paper, taking the two representative pollutants, PM2.5 and CO₂, as examples, we used the data from 2010 to 2022 and empirically examined the specific impact of urban sprawl on air pollution. Overall, urban sprawl increases pollutant emissions and exacerbates air pollution. In this process, private car usage is an important mechanism. Moreover, there is significant heterogeneity in the effects of urban sprawl on air pollution. The pollution effect of urban sprawl on the air environment is significant in the western region and small cities. Besides, urban sprawl also has a nonlinear effect on air pollution. Specifically, urban sprawl has a U-shaped effect on air pollution. Currently, the effects of urban sprawl on emissions of both pollutants lie on the right side of the curve.

Abstract

The process of urbanization is limited by the widening urban–rural gap worldwide, which needs to be improved by reconsidering the interaction between urban and rural areas dynamically and systematically. This study aims to use multidimensional connectivity network analysis to answer the role of landscape resources as a connecting medium (represented by linear canals) penetrating the urban–rural space in urban–rural integration. First, this study proposes a framework of “Urban–Canal–Rural” from a multidimensional perspective. In this research, we re-examined the urban–rural differences within the region by using the canal as the central regional conduit connecting urban and rural areas. Then, an association network based on five dimensions was constructed, and the network's connectivity was detected. In light of this, the integration characteristics and factor flow mechanism of “Urban–Canal–Rural” were revealed. Based on the study, we identified the potential interactive advantages of urban–rural integration within the canal basin, which provides the strategy for the development of “Urban–Canal–Rural” integration. The study found that within the same region, “Urban–Canal–Rural” shows completely different correlation strengths in five dimensions, revealing that the urban–rural differences in the process of urbanization are closely related to the inadequate utilization of resources. It also confirmed the importance of multidimensional network construction in balancing the allocation of resources between urban and rural areas in the process of urban–rural integration. Finally, the relations of factor mobility and resource allocation to sustainable urban and rural development were discussed. The authors argued that core resources between rural and urban areas are the key variable in restructuring rural–urban relations to achieve sustainable development. In general, urban and rural development should maintain the integrity and balance of the regional system. Additionally, this study provides Chinese experience for the worldwide study of urban–rural sustainable development.

Practical Applications

How to scrutinize the new interaction and balance between urban and rural areas is an unavoidable topic for urban and rural development. Examining the issue of urban–rural differences in the process of urbanization from a dynamic and systematic perspective, we found a close relationship between the balance and utilization of regional resources and regional differences. This paper adopted a network analysis method and proposed a framework of “Urban–Canal–Rural” from a multidimensional perspective. It aimed to use multidimensional connectivity network analysis to answer the role of landscape resources as a connecting medium (represented by linear canals) penetrating the urban–rural space in urban–rural integration. Network analysis was used to grasp the whole picture of the urban–rural spatial structure and reveal the overall characteristics of the network structure to determine the optimal network connectivity and resource allocation. This method can be used to facilitate the optimization of interregional connectivity and resource allocation approaches, as well as the formulation and communication of consensus-building processes for planning and sustainable development management. It is applicable not only in the context of this study using Jiangsu Province as a case study but also can provide a generalized policy impact and development regulation basis for projects outside of China.

While green infrastructures (GIs) are used to address urban flooding and stormwater runoff and enhance sustainability, their implementation faces challenges such as limited funding and competing priorities. Existing studies generally focused on specific/individual GI practices, potentially overlooking the broader benefits or values of comprehensive GI plans that generally are interconnected networks of multiple GI practices. Thus, this paper developed an agent-based model to offer municipalities, planners, and decision makers a structured and systematic modeling approach to: (1) simulate the dynamic nature of GI implementation plans across spatial and temporal dimensions; (2) capture the interplay among regulations that govern GI plans; and (3) conduct scenario and sensitivity analyses to gain deeper insights into the various characteristics of GI plans under different scenarios. The proposed model considered different economic values of GI plans, including stormwater management, carbon sequestration, pollutant removal, energy cost savings, and increased property value, as well as the social values, such as the positive impact on nearby residents/communities. In addition, the developed model considered the following six GI practices: green roofs, rain gardens, community gardens, bioswales, permeable playgrounds, and permeable pavements. These GI practices were modeled across five submodels: school greening, private property greening, park greening, right-of-way property greening, and public housing properties greening. Scenario analysis was conducted to investigate the effect of financial limitations (i.e., funding priorities) on the model’s behavior under two scenarios. Finally, the developed model was statistically validated. The results showed that increasing the number of GIs does not guarantee an increase in their economic value, but rather the implementation of GIs should be well planned according to a priority plan. The findings also provided valuable insights into the importance of considering physical and institutional limitations. This paper contributes a practical workflow for evaluating the costs and benefits of GI programs.

Previous studies have primarily focused on off-street parking lots, leveraging parking fees to reduce search time and enhance socioeconomic benefits. However, existing research overlooks the examination of parkers’ choice behavior within a single parking lot and fails to incorporate differential parking fees in analyzing the choices of individual parking spaces. To this end, this study introduces the multinomial logit and mixed logit models to explore the influence of variables on parkers’ choice of parking spaces. Moreover, the marginal willingness to pay is calculated for the four variables (i.e., parking fee, mechanical space, walking time, and search time) for work and recreation purposes to determine how much parkers are willing to spend for them. The results show that all four variables have a significant negative effect on parker’s choice, and mechanical parking space is core for parkers.

The classification of urban functional zones helps to understand the spatial structure of urban functions. However, achieving high classification accuracy is challenging, because of the complexity and randomness of urban components and their spatial distribution. An important idea in existing urban functional zone classification research is to extract the spatial context of points of interest (POIs) based on their spatial relationships, embed the POI representations, and then calculate the vector representation of the urban functional zones for classification. Important features that could be extracted from the spatial relationships between the POIs are the homogeneity and structural similarity between POIs. Although their important impact on urban functional zone classification has received attention, most studies construct urban functional zone classification methods that are based on the homogeneity of POIs. Limited studies combine them to construct urban functional zone classification methods. In this paper, a novel method for urban functional zone classification was proposed by integrating the homogeneity and structural similarity between POIs. First, the neighborhood structure of the POIs is defined based on the spatial relationships between POIs. Second, biased random walking strategies are designed to generate the spatial contexts of POIs. Third, the spatial contexts of the POIs are input into the Skip-Gram model to generate vectors for the POI types. Then, the vectors of urban functional zones are calculated. Finally, the support vector machine (SVM) is used for urban functional zone classification that is based on their vectors. The model was applied in Chaoyang District, Beijing. The feasibility, accuracy, and stability of the model were verified by comparing it with the Place2vec and the DeepWalk models.

Urban assessment is an important basis for judging the sustainable development capability of cities. This study constructs an urban assessment index system from six aspects: health and comfort, ecological livability, convenient transportation, cleanliness and orderliness, diversity and inclusiveness, and innovation and vitality. Based on the spatial panel data of 286 prefecture-level cities in China from 2011 to 2021, the spatial differences that exist in urban appraisal among the three major regions of China and their convergence are investigated. The study shows the following: First, the study reveals a significant improvement in the level of city governance across the country, with a gradual reduction in absolute differences. Second, the overall differences in the urban assessment scores of individual cities in China have been decreasing year by year. Intraregional differences are smaller than interregional differences, with the east-central region showing the largest interregional difference. Third, regarding σ convergence, the evolutionary trends of city governance levels in the nation and the eastern, central, and western parts of China are somewhat turbulent but show significant σ convergence characteristics overall. Absolute spatial β-convergence coefficients in the nation and the eastern, central, and western parts of China are significantly smaller than 0. Additionally, there are conditional β-convergence trends in city governance in the nation and each city in the eastern, central, and western parts of China.

Urban construction is confronted with increasingly complex challenges as social and economic development progresses. Urban regeneration has become an inevitable choice for promoting high-quality urban development in the new era. Historical and cultural districts, with historic buildings as spatial carriers, are microcosms of a city’s development and a testimony to the lives of local people. It is necessary to define their development position, role in the city, and functions to revitalize them commercially. The best way to achieve these goals is to clarify consumer preferences and identify the key factors that influence target groups’ behavioral preferences in similar shopping areas. Only then will we be able to truly preserve the character and value of heritage districts while promoting their commercial development. This paper focuses on heritage districts. Through a combination of online and offline questionnaires, the authors learned about the current situation of young consumer behavioral preferences for urban commercial revitalization projects. A theory of planned behavior model was then built to empirically analyze the factors influencing consumer behavioral preferences in these projects. Based on the results of our analysis, we propose goals and suggestions for the government, property developers, and citizens involved in revitalization projects to support urban commercial revitalization and promote consumers’ consumption intentions. Governments emphasize the importance of culture and give more directions to maintain historical elements. From the perspective of property developers, a business format combining culture and the market is necessary. The participation of citizens in the process of urbanization leads to a people-oriented and sustainable strategy that is beneficial for future development.

A resilient city is a key goal of the country’s high-quality development and could effectively reduce city disaster losses. However, due to the significant spatial differences in China’s urban development, research on resilience has mainly focused on developed regions in Eastern China. Therefore, this paper takes Chongqing, a typical city in Western China, as the study area and evaluates the level of urban resilience from four dimensions: (1) economic; (2) social; (3) ecological; and (3) technological. The entropy weight method and exploratory spatial data analysis (ESDA) are applied to identify its spatial and temporal evolution characteristics and regional heterogeneity, and the obstacle degree model is applied to diagnose its main obstacle factors to improve the city’s resilience in a reverse direction. The results show that in the time dimension, Chongqing’s urban resilience level shows yearly growth and economic resilience is the main factor in the improvement of the urban resilience level. In the spatial dimension, the western part of the city is higher than the eastern part, which shows the nonequilibrium phenomenon of high-value agglomeration and low-value dispersion, which has a significant spatial spillover effect. For the obstacle factors, the degree of obstruction at the guideline level is in the order of social > economic > technological > ecological, and the public library collection and the balance of RMB deposits are the main factors that restrict the resilience of cities. Performing the resilience evaluation for typical cities could identify the weak links in resilience in different dimensions and provide a theoretical basis for the governmental decision-making and resource allocation for cities that are under sudden risk disasters.

As a crucial measure to promote the coordinated development of urban and rural areas in developing countries (such as China), how to provide and manage rural infrastructure investment is a major challenge. In line with the implementation of a coordinated urban–rural development strategy, inclusive growth provides direction for rural infrastructure investment. Taking Chongqing, China, as an example, informed by the goals of inclusive growth, this study develops a system dynamics model to investigate the interaction between interdependent infrastructure systems and socioeconomic systems and to explore priorities for rural infrastructure investment. The results indicate the following: (1) more rural infrastructure investment is still needed in Chongqing by 2030; and (2) based on the importance of all types of rural infrastructures for the impact of inclusive growth goals, the ratio of budget shares invested in each dimension is, in descending order, environment infrastructure, energy infrastructure, communication infrastructure, transportation infrastructure, education infrastructure, and medical infrastructure. The approach and results of this study allow governments to assess the contribution of infrastructure provision to the goals of inclusive growth and to make better-informed infrastructure investment options.

Abstract

People's livelihood issues are related to their basic needs and interests, and the use of information and communication technologies (ICTs), which enable citizens to actively participate in the governance of people's livelihood issues, has revolutionized the paradigm of managing and regulating affairs and issues in the city. Although livelihood issues are different from physical objects, they occur in a specific space, are still affected by many geospatial factors, and should also exhibit specific spatial characteristics. To investigate the spatial characteristics and influencing factors of livelihood issues in the main urban areas of Chengdu City, the study was based on the data of livelihood issues in Chengdu City's online governance platform. First, it explored the spatial and temporal distribution characteristics of livelihood issues in the main urban areas of Chengdu City by using spatial analysis. It then analyzed the influencing factors of the spatial differentiation of livelihood issues by using text analysis and Geodetectors, and finally put forward the countermeasures for governance of livelihood issues. The results show that holidays and temperature changes may affect the intensity of people's daily activities and regulate the periodicity of production and life, causing the number of livelihood issues to change with the seasons, showing an increase in the number of livelihood issues in spring and fall, and a decrease in the number of livelihood issues in summer and winter. The cold spots and hot spots of livelihood issues are characterized by marginalization and concentration in space. The livelihood issues in the categories of residents' life, road traffic, housing and land, social service, city environment, and building production are spatially clustered, with the kernel density values decreasing from the center to the periphery, and the high-value areas dispersed in the form of small clusters. The overall explanatory power of commercial conditions and public service conditions in explaining the spatial differentiation of livelihood issues surpasses that of demographic conditions and traffic conditions. This study expands the research path of livelihood issues, enriches the data sources, and supplements the research on livelihood issues at small scales with subdistricts as the research unit. The study's findings can aid in identifying the spatial and temporal patterns of livelihood issues, and serve as a foundation for devising strategies to prevent and address livelihood issues.

Practical Applications

In the context of the digital era, the application of an online governance platform makes urban governance more intelligent and efficient. As a critical component of urban governance, livelihood issues are inextricably linked to people's daily lives. The majority of current research focuses on the governance of livelihood issues; nevertheless, there is still a lack of research into whether livelihood issues have specific spatial characteristics and what variables influence their spatial distribution. We collected data on livelihood issues with spatial attributes using an online governance platform. After conducting spatial analysis, we discovered that the characteristics of the spatial distribution of livelihood issues show the marginalization and concentration of subdistricts with low rates of livelihood issues and notably concentrated livelihood issues, and that livelihood issues are more frequent at the junction of subdistricts. The density of commercial and public service facilities has a stronger influence on the distribution of livelihood issues than the density of transportation and demographic conditions. This study takes a novel approach to studying livelihood issues by conducting in-depth analyses of spatial and temporal distribution characteristics, as well as influencing factors, and can serve as a foundation for the development of urban governance countermeasures, thereby improving the effectiveness of urban governance and urban development quality.

The government-led mode of urban renewal plays an important role in assisting less profitable projects in addressing the problems of urban decay and promoting the intensive use of land. However, the imbalance between the benefit distribution for multiple stakeholders hinders the success of urban renewal projects. This study initially proposed a theoretical model of a dynamic game among the government, developers, and residents in government-led projects, which was validated by a case study on Liede Village, Guangzhou, China. This study identified the critical factors that influence the payoff in the proportion of construction land, which includes a comprehensive plot ratio (CPR) for commercial construction land and resettlement housing land. Sensitivity analysis and Monte Carlo experiments were conducted to measure the influence of these factors on benefit distribution. The results suggested that conflicts exist in the proportional distribution of construction land, and the increase in the CPR could compensate for the loss of the land proportion. Finally, strategies for balancing benefit distribution among stakeholders were proposed to help the government sector mitigate the financial burden and ensure public interest in urban renewal.

Homeownership rates have declined, underscoring the significant challenges our society faces in affording homes. This research aims to develop an effective and precise tool for swiftly evaluating and filtering out unqualified applications and establish consistent review criteria for cities and townships across Taiwan. The proposed approach involves the creation of a tool that utilizes particle swarm optimization-based fuzzy hyperrectangular composite neural networks. This paper, chosen without political bias and based on a randomly selected year, uses a data set of 36,086 entries from across Taiwan, with each application containing 10 distinct features for further analysis. The result achieves an impressive accuracy rate of 98.6% and produces 66 recommended rules for determining eligibility for rental subsidies. The contributions of this study are twofold: (1) the rapid auditing tool benefits both government agencies and applicants, streamlining the application process; and (2) the 66 rules generated by the tool offer valuable guidance to internal auditors, expediting audits and reducing personal biases. This promotes a more standardized and efficient workflow.

Historic urban areas are unique spaces that carry collective memories and cultural identities, and their spatial quality significantly contributes to urban development and vitality. The sustainable development of these areas is a complex subject that continually garners attention in the field of urban planning. Optimizing their spatial quality necessitates an in-depth understanding of public needs, along with careful consideration of the connection between physical attributes and public perception. Advancements in big data and machine learning have paved the way for the multidimensional evaluation of spatial quality in historic urban areas. In this light, our research proposed a new evaluation system and optimization strategy rooted in the unique attributes and cultural values of these areas. Our empirical research focused on Suzhou Ancient Urban, a representative historic urban area in China. First, we identified six indicators, including appearance, order, atmosphere, and scale, to evaluate the public's perception of the streets in Suzhou Ancient Urban, a place rich with cultural history and local characteristics. This evaluation resulted in a perception map of this area. Second, we explored the unique planning structure, functional distribution, and visual elements of Suzhou Ancient Urban. Using spatial syntax, points of interest (POIs), social media post data processed via natural language processing (SnowNLP), and semantic segmentation methods, we connected the physical attributes of the area with public behavioral preferences and perceptions. This macro-to-micro approach combined subjective and objective evaluations to measure spatial quality. Finally, we established a database for organic urban renewal, which highlights the spatial characteristics of historic urban areas that the public preferred. Our findings indicate that the spaces with higher accessibility in Suzhou Ancient Urban scored better in terms of overall perception. Furthermore, highly distinctive and accessible spaces were the most attractive to the public. Elements such as buildings and walls negatively impacted perception, while infrastructure elements such as roads, pavements, and greenery had a positive effect. This research evaluated the spatial quality of streets in historic urban areas with a special focus on public perception. By combining objective factors such as street accessibility, attractiveness, and visual elements, we discuss the influence of urban structure, function, and components on spatial quality. Our approach, founded on the specific spatial–geographical context of historic urban areas, offered a new methodology for optimizing their quality by integrating subjective and objective factors. Ultimately, our research aimed to foster digital and sustainable development in historic urban areas.

The traffic planning network (TPN) represents future urban development and holds particular significance for the growth of cities. Although urban morphology (UM) has been applied to traffic networks, there exists a lack of multiscale quantitative research on TPN. From the UM perspective, this paper develops a quantitative framework to achieve the extraction and analysis of multimorphological features of TPNs on spatiotemporal scales. Subsequently, we investigated the morphological evolution of TPNs in Nanjing, China, from the 1980s to the 2020s. The research reveals the following findings: (1) In terms of spatiotemporal scales, the Nanjing TPN exhibits a multicentric agglomeration pattern on a smaller scale, evolving from discrete points to urban belts; on a larger scale, the urban framework transitions from a cross-shaped axis to a circular radial form. The evolution of Nanjing's form zones shows a southward shift of the Core zone and a transition from agglomeration to expansion and then gradual stabilization in the periphery of the Core zone. (2) The quantitative framework we proposed effectively extracts morphological characteristics within TPNs, visualizing the focal points and trends in urban traffic planning. (3) These morphological characteristics create Nanjing's heart-shaped layout, also reflecting the evolution of planning concepts from concentric urban groups to urban–rural integration. Our study enriches research on traffic planning and UM and offers valuable insights for traffic planning in Chinese cities.